Search (322 results, page 1 of 17)

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Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

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Abstract

The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.

Theme

Social tagging

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Abstract

Purpose - The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts. Design/methodology/approach - Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer. Findings - The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals. Originality/value - This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

Date

20. 1.2015 18:30:22

Footnote

Teil eines Special Issue: Social Media Metrics in Scholarly Communication: exploring tweets, blogs, likes and other altmetrics.

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Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

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Abstract

Aggregated journal-journal citations can be used for mapping the intellectual organization of the sciences in terms of specialties because the latter can be considered as interreading communities. Can the journal-journal citations also be used as early indicators of change by comparing the files for two subsequent years? Probabilistic entropy measures enable us to analyze changes in large datasets at different levels of aggregation and in considerable detail. Compares Journal Citation Reports of the Social Science Citation Index for 1999 with similar data for 1998 and analyzes the differences using these measures. Compares the various indicators with similar developments in the Science Citation Index. Specialty formation seems a more important mechanism in the development of the social sciences than in the natural and life sciences, but the developments in the social sciences are volatile. The use of aggregate statistics based on the Science Citation Index is ill-advised in the case of the social sciences because of structural differences in the underlying dynamics.

Date

6.11.2005 19:02:22

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Abstract

Interdisciplinary research is widely recognized as necessary to tackle some of the grand challenges facing humanity. It is generally believed that interdisciplinarity is becoming increasingly prevalent among Science, Technology, Engineering, and Mathematics (STEM) fields. However, little is known about the evolution of interdisciplinarity in the Social Sciences. Also, how interdisciplinarity and its various aspects evolve over time has seldom been closely quantified and delineated. This paper answers these questions by capturing the disciplinary diversity of the knowledge base of scientific publications in nine broad Social Sciences fields over 55 years. The analysis considers diversity as a whole and its three distinct aspects, namely variety, balance, and disparity. Ordinary least squares (OLS) regressions are also conducted to investigate whether such change, if any, can be found among research with similar characteristics. We find that learning widely and digging deeply have become one of the norms among researchers in Social Sciences. Fields acting as knowledge exporters or independent domains maintain a relatively stable homogeneity in their knowledge base while the knowledge base of importer disciplines evolves towards greater heterogeneity. However, the increase of interdisciplinarity is substantially smaller when controlling for several author and publication related variables.

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Abstract

Although there is evidence that counting the readers of an article in the social reference site, Mendeley, may help to capture its research impact, the extent to which this is true for different scientific fields is unknown. In this study, we compare Mendeley readership counts with citations for different social sciences and humanities disciplines. The overall correlation between Mendeley readership counts and citations for the social sciences was higher than for the humanities. Low and medium correlations between Mendeley bookmarks and citation counts in all the investigated disciplines suggest that these measures reflect different aspects of research impact. Mendeley data were also used to discover patterns of information flow between scientific fields. Comparing information flows based on Mendeley bookmarking data and cross-disciplinary citation analysis for the disciplines revealed substantial similarities and some differences. Thus, the evidence from this study suggests that Mendeley readership data could be used to help capture knowledge transfer across scientific disciplines, especially for people that read but do not author articles, as well as giving impact evidence at an earlier stage than is possible with citation counts.

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Abstract

This is a study of coverage and overlap in second-generation social sciences and humanities journal lists, with attention paid to curation and the judgment of scholarliness. We identify four factors underpinning coverage shortfalls: journal language, country, publisher size, and age. Analyzing these factors turns our attention to the process of assessing a journal as scholarly, which is a necessary foundation for every list of scholarly journals. Although scholarliness should be a quality inherent in the journal, coverage falls short because groups assessing scholarliness have different perspectives on the social sciences and humanities literature. That the four factors shape perspectives on the literature points to a deeper problem of fragmentation within the scholarly community. We propose reducing this fragmentation as the best method to reduce coverage shortfalls.

Date

22. 1.2011 13:21:28

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Abstract

To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.

Date

21. 3.2023 19:22:14

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Abstract

This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.

Content

1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.

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Abstract

This paper uncovers patterns of knowledge dissemination among scientific disciplines. Although the transfer of knowledge is largely unobservable, citations from one discipline to another have been proven to be an effective proxy to study disciplinary knowledge flow. This study constructs a knowledge-flow network in which a node represents a Journal Citation Reports subject category and a link denotes the citations from one subject category to another. Using the concept of shortest path, several quantitative measurements are proposed and applied to a knowledge-flow network. Based on an examination of subject categories in Journal Citation Reports, this study indicates that social science domains tend to be more self-contained, so it is more difficult for knowledge from other domains to flow into them; at the same time, knowledge from science domains, such as biomedicine-, chemistry-, and physics-related domains, can access and be accessed by other domains more easily. This study also shows that social science domains are more disunified than science domains, because three fifths of the knowledge paths from one social science domain to another require at least one science domain to serve as an intermediate. This work contributes to discussions on disciplinarity and interdisciplinarity by providing empirical analysis.

Date

26.10.2014 20:22:22

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Abstract

According to Jean M. Tague-Sutcliffe "informetrics" is "the study of the quantitative aspects of information in any form, not just records or bibliographies, and in any social group, not just scientists" (Tague-Sutcliffe, 1992, 1). Leo Egghe also defines "informetrics" in a very broad sense. "(W)e will use the term' informetrics' as the broad term comprising all-metrics studies related to information science, including bibliometrics (bibliographies, libraries,...), scientometrics (science policy, citation analysis, research evaluation,...), webometrics (metrics of the web, the Internet or other social networks such as citation or collaboration networks), ..." (Egghe, 2005b,1311). According to Concepcion S. Wilson "informetrics" is "the quantitative study of collections of moderatesized units of potentially informative text, directed to the scientific understanding of information processes at the social level" (Wilson, 1999, 211). We should add to Wilson's units of text also digital collections of images, videos, spoken documents and music. Dietmar Wolfram divides "informetrics" into two aspects, "system-based characteristics that arise from the documentary content of IR systems and how they are indexed, and usage-based characteristics that arise how users interact with system content and the system interfaces that provide access to the content" (Wolfram, 2003, 6). We would like to follow Tague-Sutcliffe, Egghe, Wilson and Wolfram (and others, for example Björneborn & Ingwersen, 2004) and call this broad research of empirical information science "informetrics". Informetrics includes therefore all quantitative studies in information science. If a scientist performs scientific investigations empirically, e.g. on information users' behavior, on scientific impact of academic journals, on the development of the patent application activity of a company, on links of Web pages, on the temporal distribution of blog postings discussing a given topic, on availability, recall and precision of retrieval systems, on usability of Web sites, and so on, he or she contributes to informetrics. We see three subject areas in information science in which such quantitative research takes place, - information users and information usage, - evaluation of information systems, - information itself, Following Wolfram's article, we divide his system-based characteristics into the "information itself "-category and the "information system"-category. Figure 1 is a simplistic graph of subjects and research areas of informetrics as an empirical information science.

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Abstract

Recent studies have shown that counting citations from books can help scholarly impact assessment and that Google Books (GB) is a useful source of such citation counts, despite its lack of a public citation index. Searching GB for citations produces approximate matches, however, and so its raw results need time-consuming human filtering. In response, this article introduces a method to automatically remove false and irrelevant matches from GB citation searches in addition to introducing refinements to a previous GB manual citation extraction method. The method was evaluated by manual checking of sampled GB results and comparing citations to about 14,500 monographs in the Thomson Reuters Book Citation Index (BKCI) against automatically extracted citations from GB across 24 subject areas. GB citations were 103% to 137% as numerous as BKCI citations in the humanities, except for tourism (72%) and linguistics (91%), 46% to 85% in social sciences, but only 8% to 53% in the sciences. In all cases, however, GB had substantially more citing books than did BKCI, with BKCI's results coming predominantly from journal articles. Moderate correlations between the GB and BKCI citation counts in social sciences and humanities, with most BKCI results coming from journal articles rather than books, suggests that they could measure the different aspects of impact, however.

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Abstract

This article challenges recent research (Evans, 2008) reporting that the concentration of cited scientific literature increases with the online availability of articles and journals. Using Thomson Reuters' Web of Science, the present article analyses changes in the concentration of citations received (2- and 5-year citation windows) by papers published between 1900 and 2005. Three measures of concentration are used: the percentage of papers that received at least one citation (cited papers); the percentage of papers needed to account for 20%, 50%, and 80% of the citations; and the Herfindahl-Hirschman index (HHI). These measures are used for four broad disciplines: natural sciences and engineering, medical fields, social sciences, and the humanities. All these measures converge and show that, contrary to what was reported by Evans, the dispersion of citations is actually increasing.

Date

22. 3.2009 19:22:35

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Abstract

One of the solutions to help scientists filter the most relevant publications and, thus, to stay current on developments in their fields during the transition from "little science" to "big science", was the introduction of citation indexing as a Wellsian "World Brain" (Garfield, 1964) of scientific information: It is too much to expect a research worker to spend an inordinate amount of time searching for the bibliographic descendants of antecedent papers. It would not be excessive to demand that the thorough scholar check all papers that have cited or criticized such papers, if they could be located quickly. The citation index makes this check practicable (Garfield, 1955, p. 108). In retrospective, citation indexing can be perceived as a pre-social web version of crowdsourcing, as it is based on the concept that the community of citing authors outperforms indexers in highlighting cognitive links between papers, particularly on the level of specific ideas and concepts (Garfield, 1983). Over the last 50 years, citation analysis and more generally, bibliometric methods, have developed from information retrieval tools to research evaluation metrics, where they are presumed to make scientific funding more efficient and effective (Moed, 2006). However, the dominance of bibliometric indicators in research evaluation has also led to significant goal displacement (Merton, 1957) and the oversimplification of notions of "research productivity" and "scientific quality", creating adverse effects such as salami publishing, honorary authorships, citation cartels, and misuse of indicators (Binswanger, 2015; Cronin and Sugimoto, 2014; Frey and Osterloh, 2006; Haustein and Larivière, 2015; Weingart, 2005).
Furthermore, the rise of the web, and subsequently, the social web, has challenged the quasi-monopolistic status of the journal as the main form of scholarly communication and citation indices as the primary assessment mechanisms. Scientific communication is becoming more open, transparent, and diverse: publications are increasingly open access; manuscripts, presentations, code, and data are shared online; research ideas and results are discussed and criticized openly on blogs; and new peer review experiments, with open post publication assessment by anonymous or non-anonymous referees, are underway. The diversification of scholarly production and assessment, paired with the increasing speed of the communication process, leads to an increased information overload (Bawden and Robinson, 2008), demanding new filters. The concept of altmetrics, short for alternative (to citation) metrics, was created out of an attempt to provide a filter (Priem et al., 2010) and to steer against the oversimplification of the measurement of scientific success solely on the basis of number of journal articles published and citations received, by considering a wider range of research outputs and metrics (Piwowar, 2013). Although the term altmetrics was introduced in a tweet in 2010 (Priem, 2010), the idea of capturing traces - "polymorphous mentioning" (Cronin et al., 1998, p. 1320) - of scholars and their documents on the web to measure "impact" of science in a broader manner than citations was introduced years before, largely in the context of webometrics (Almind and Ingwersen, 1997; Thelwall et al., 2005):
There will soon be a critical mass of web-based digital objects and usage statistics on which to model scholars' communication behaviors - publishing, posting, blogging, scanning, reading, downloading, glossing, linking, citing, recommending, acknowledging - and with which to track their scholarly influence and impact, broadly conceived and broadly felt (Cronin, 2005, p. 196). A decade after Cronin's prediction and five years after the coining of altmetrics, the time seems ripe to reflect upon the role of social media in scholarly communication. This Special Issue does so by providing an overview of current research on the indicators and metrics grouped under the umbrella term of altmetrics, on their relationships with traditional indicators of scientific activity, and on the uses that are made of the various social media platforms - on which these indicators are based - by scientists of various disciplines.

Date

20. 1.2015 18:30:22

Footnote

Teil eines Special Issue: Social Media Metrics in Scholarly Communication: exploring tweets, blogs, likes and other altmetrics. Der Beitrag ist frei verfügbar.

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Abstract

Purpose The purpose of this paper is to analyze the capabilities, functionalities and appropriateness of Altmetric.com as a data source for the bibliometric analysis of books in comparison to PlumX. Design/methodology/approach The authors perform an exploratory analysis on the metrics the Altmetric Explorer for Institutions, platform offers for books. The authors use two distinct data sets of books. On the one hand, the authors analyze the Book Collection included in Altmetric.com. On the other hand, the authors use Clarivate's Master Book List, to analyze Altmetric.com's capabilities to download and merge data with external databases. Finally, the authors compare the findings with those obtained in a previous study performed in PlumX. Findings Altmetric.com combines and orderly tracks a set of data sources combined by DOI identifiers to retrieve metadata from books, being Google Books its main provider. It also retrieves information from commercial publishers and from some Open Access initiatives, including those led by university libraries, such as Harvard Library. We find issues with linkages between records and mentions or ISBN discrepancies. Furthermore, the authors find that automatic bots affect greatly Wikipedia mentions to books. The comparison with PlumX suggests that none of these tools provide a complete picture of the social attention generated by books and are rather complementary than comparable tools. Practical implications This study targets different audience which can benefit from the findings. First, bibliometricians and researchers who seek for alternative sources to develop bibliometric analyses of books, with a special focus on the Social Sciences and Humanities fields. Second, librarians and research managers who are the main clients to which these tools are directed. Third, Altmetric.com itself as well as other altmetric providers who might get a better understanding of the limitations users encounter and improve this promising tool. Originality/value This is the first study to analyze Altmetric.com's functionalities and capabilities for providing metric data for books and to compare results from this platform, with those obtained via PlumX.

Content

Teil eines Special Issue: Scholarly books and their evaluation context in the social sciences and humanities. Vgl.: https://doi.org/10.1108/AJIM-06-2018-0152.

Date

20. 1.2015 18:30:22

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Abstract

Examines the use of networked information sources in scholarly communication. Networked information sources are defined broadly to cover: documents and images stored on electronic network hosts; data files; newsgroups; listservs; online information services and electronic periodicals. Reports results of a survey to determine how heavily, if at all, networked information sources are cited in scholarly printed periodicals published in 1993 and 1994. 27 printed periodicals, representing a wide range of subjects and the most influential periodicals in their fields, were identified through the Science Citation Index and Social Science Citation Index Journal Citation Reports. 97 articles were selected for further review and references, footnotes and bibliographies were checked for references to networked information sources. Only 2 articles were found to contain such references. Concludes that, although networked information sources facilitate scholars' work to a great extent during the research process, scholars have yet to incorporate such sources in the bibliographies of their published articles

Source

IFLA journal. 22(1996) no.3, S.240-245

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Abstract

University librarians continue to face the difficult task of determining which journals remain crucial for their collections during these times of static financial resources and escalating journal costs. One evaluative tool, Journal Citation Reports (JCR), recently has become available on CD-ROM, making it simpler for librarians to use its citation data as input for ranking journals. But many librarians remain unconvinced that the global citation data from the JCR bears enough correspondence to their local situation to be useful. In this project, I explore the correlation between global citation data available from JCR with local citation data generated specifically for the University of British Columbia, for 20 subject fields in the sciences and social sciences. The significant correlations obtained in this study suggest that large research-oriented university libraries could consider substituting global citation data for local citation data when evaluating their journals, with certain cautions.

Date

10. 9.2000 17:38:22

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Abstract

Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations.

Date

28. 9.2010 12:54:22

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Abstract

Purpose - The purpose of this paper is to attempt to provide a review of the growing literature on co-authorship networks and the research gaps that may be investigated for future studies in this field. Design/methodology/approach - The existing literature on co-authorship networks was identified, evaluated and interpreted. Narrative review style was followed. Findings - Co-authorship, a proxy of research collaboration, is a key mechanism that links different sets of talent to produce a research output. Co-authorship could also be seen from the perspective of social networks. An in-depth analysis of such knowledge networks provides an opportunity to investigate its structure. Patterns of these relationships could reveal, for example, the mechanism that shapes our scientific community. The study provides a review of the expanding literature on co-authorship networks. Originality/value - This is one of the first comprehensive reviews of network-based studies on co-authorship. The field is fast evolving, opening new gaps for potential research. The study identifies some of these gaps.

Date

20. 1.2015 18:30:22